Instructions to use hf-internal-testing/tiny-random-IBertForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-IBertForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-internal-testing/tiny-random-IBertForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-IBertForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-internal-testing/tiny-random-IBertForTokenClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a99a01f3d9f626cb97faa349796443ef9169c81add63388b11cd11dd8ee5c21f
- Size of remote file:
- 1.2 MB
- SHA256:
- 7ceb481940902b0c847a5d77b990a625dcfe7979006dc1683abf1d25abb16c03
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